Impact of climate change in Thailand and globally

2.1

Climate and Impacts Observations

A systematic study which can explain past and present climate phenomena that are linked to changes and impacts that may occur in the future

2.2

Climate Model

Mathematical models which use quantitative data to simulate the interaction of energy in the atmosphere, oceans, ground, and ice sheets

2.3

Projection of greenhouse gas emissions

Projection of GHG emission considers results of complex systems and dynamics from population, economic, social and technology development

2.4

Global Climate Change from the Past to the Present

Historical data from past to present about the trends and details of global climate change

2.5

Trends of Change and Effects on the World in the Future

Report of the key findings in the 5th Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) on global climate change trends

2.6

Current climate change trends in Thailand

Current climate change trends in Thailand from the 1st and 2nd Thailand Climate Change Knowledge Synthesis and Knowledge Assessment Report

2.7

Future climate change trends in Thailand

Simulation of future climate change trends in Thailand under the GHG emission of RCP4.5 and RCP8.5 scenarios

2.8

Variation and Climate Phenomena Linking Climate Change in Thailand

Climate variability to climate patterns that deviate from normal values and can last annually to many decades and it is the result of global, regional and local climate phenomena

2.1

Climate and Impacts Observations

The observations of Climate Change is systematic, relying on phenomena of the past and present climatic conditions that are linked to future changes, the steps of climate and impacts observations are divided as follows;
    1. Paleoclimatology is the study of past climates using proxies of physical, chemical, and biological materials such as annual rings, pollen and stalactites etc.
    2. Climate Projection is the study of future climate trend using climate models that are simulated under different greenhouse gas levels, which depend on different social and economic development models of the world.
    3. Climate change impact assessment is an analysis of the vulnerabilities and risks of systems and communities by considering exposure, sensitivity, capacity including evaluating and specifying adaptation options, establishing guidelines for policies and measurement implementation. The conceptual framework can be divided into:
  1. Long-term impact assessment with projection data on future climate change at the national and local level or impact-based approach to estimate impacts that may occur under different climate change situations including assessing the physical, socio-economic impact by region in order to set adaptation guidelines to such effects, which cannot clearly identify changes in the short-term and at the local level and;
  2. Vulnerability-based approach for short-term vulnerability at the local level is an analysis of the vulnerability of current communities in a risk context of economic and social conditions, to consider the community exposure and their ability to adapt in the near future by evaluating information at the community level and participatory process.

Observation process

The main climate change observation process consists of:

  1.  Identify causes/sources/amount of greenhouse gas emissions including the mitigation potentials and measures;
  2. Conduct the climate projection by using the past-present observed values in order to create the climate models;
  3. Conduct the impact/vulnerability analysis and risk assessment regarding to the modelling results and;
  4. Develop the Management and Evaluation (M&E) and adaptation guideline, as shown in Figure 5-8.
Figure 5-8. The main steps of climate change study.
2.2

Climate Model

Climate model Is a mathematical model that uses quantitative data to simulate the interaction of energy in the atmosphere, oceans, land and ice sheets. This mode is used to study various aspects of the climate system especially the study of climate dynamics and projections of future changes. All kinds of climate models use the principles of equilibrium of world energy. For example, incoming energy to the earth from the sun in the form of short-wave radiation and transfer of energy outside the Earth’s atmosphere in the form of long-wave radiation or heat radiation. The imbalance of energy entering the earth and exporting from the earth with various processes on the surface of the earth results in variations and climate change conditions. Increasing greenhouse gases from human activities and changes in land-use are the main driving forces used in climate models for projections of future changes.

Creating climate change models requires basic knowledge of climate science. Climate models are necessary tools to cope systematically with the impacts of climate change according to academic principles. Studies in this field have been developed and continuously gain new knowledge. The Intergovernmental Panel on Climate Change (IPCC) has reviewed and synthesized knowledge and created images from climate models which have regularly been published in their reports.

2.3

Projection of greenhouse gas emissions

Projection of greenhouse gas emissions consider results of complex systems and dynamics from population, economic, social and technological development. There is a high uncertainty of greenhouse gases changing in the future depending on the pattern and direction of world economic development and due to the increasing population. The projection of future greenhouse gas emissions is considered an alternative image that may occur in the future and is a suitable tool for determining the driving force which may affect the greenhouse gas emissions and assess related vulnerability. The projection also helps to analyse climate change including the creation of climate models and impact assessment, adaptation and reduction of greenhouse gas emissions

IPCC Special Report on Emissions Scenarios

The SRES has simulated future greenhouse gas emissions under different circumstances of economic and social development guidelines and cooperation into 4 sets. The details of each scenario are summarized as follows (Figure 5-9):
  • High Greenhouse gas emissions – A1- describes a future world of very rapid economic growth, global population that peaks in the mid-century and declines thereafter, and the rapid introduction of new and more efficient technologies.
  • High-medium greenhouse gas emissions – A2 – describes a case of economic development which is primarily regionally oriented and per capita economic growth and technological change are more fragmented and slower than in other sets. Fertility patterns across regions converge very slowly, which results in continuously increasing global population.
  • Low greenhouse gas emissions – B1 – describes rapid changes in economic structures toward a service and information economy, with reductions in material intensity, and the introduction of clean and resource-efficient technologies. The emphasis is on global solutions to economic, social, and environmental sustainability, including improved equity, but without additional climate initiatives with the same global population that peaks in the mid-century and declines thereafter, as in A1.
  • Moderate-low greenhouse gas emissions – B2 – describes a world in which the emphasis is on local solutions to economic, social, and environmental sustainability. It is a world with a continuously increasing global population at a rate lower than A2, intermediate levels of economic development, and less rapid and more diverse technological change than in B1 and A1.
 
Reference:
  1. Kansri Boonprakob, 2010. Basic knowledge about climate change models in Thailand climate change information volume 2: climate model and future climate. The Thailand Research Fund. [Amnat Chidthaisong (Author)]
  2. Office of Natural Resources and Environmental Policy and Planning, 2016. The study for National Adaptation Plan PhaseII.
Figure 5-9 Future greenhouse gas emission images in the form of IPCC Special Report on Emission Scenario: SRES (IPCC, 2001)

Representative Concentration Pathway

Change (AR5). The Representative Concentration Pathways (RCPs), which are used for making projections based on these factors, describe four different 21st century pathways of GHG emissions and atmospheric concentrations, air pollutant emissions and land use. The RCPs include a stringent mitigation scenario (RCP2.6), two intermediate scenarios (RCP4.5 and RCP6.0) and one scenario with very high GHG emissions (RCP8.5). This new greenhouse gas emission projection is used as a driving force in climate modelling for simulating future climate change in order to study the impacts and vulnerabilities that may occur as in Figure 5-10.
Each RCP level has the following details: RCP2.6RCP2.6: pathway with increased radiation force until the maximum value of about 3.0 watts per square meter before the year 2100. The CO2-equivalent concentrations are about 490 ppm and decreasing afterwards until 2.6 watts per square meter or CO2-equivalent concentrations in 2100 of about 475 ppm. From the RCP2.6 showed the highest greenhouse gas emissions in the years 2010 – 2020 and decrease within the year 2100
RCP4.5 pathway of the radiation force increased to 4.5 watts per square meter in the year 2100 and constant after the year 2100. The greenhouse gas concentration in the atmosphere related to the radiation force in the year 2100 is approximately 650 ppm CO2-equivalent. From the RCP4.5, the highest greenhouse gas emissions are released in 2040 and 2080 and the emission rate will maintain until the year 2100, after which it begins to be stable and decreases respectively.
RCP6.0 pathway with increased radiation force until 6.0 watts per square meter in the year 2100 and constant after the year 2100. The concentration of greenhouse gases in the atmosphere in relation to the radiation force in the year 2100 has approximately 850 ppm CO2-equivalent. From the RCP6.0, the highest greenhouse gas emissions are release in 2040 and 2080 and the emissions rate Topic Content Note will maintain until the year 2100, thereafter it begins to be stable and decreases respectively.
RCP8.5 pathway with increased radiation force until 8.5 watts per square meter in the year 2100 and continues increasing after that. The concentration of greenhouse gases in the atmosphere relative to the radiation force in the year 2100 is approximately 1,370 ppm CO2-equivalent as shown in Figure 5-10.
Figure 5-10 Projection of greenhouse gas emissions using Representative Concentration Pathway or RCPs.
2.4

Climate change observation data from past to present

Thailand’s second assessment report on climate change 2016 namely: Updated Climate Change Knowledge and Information of Thailand prepared by the working group 1, the Thailand Research Fund or currently is Thailand Science Research and Innovation (TSRI), summarized the key findings in the 5th report of the Intergovernmental Panel on Climate Change (IPCC) on key issues Climate change of the world from the past to the present (Figure 5-11) which can be summarized as follows;
Figure 5-11. Observed changes in climate from past to present (Source: IPCC-WGI’s AR5, 2013)
Table 5-2 Trends and details of global climate change in the past
ChangeDetail
Temperature
  • Between 1880 and 2012, average temperatures over land and oceans increased 0.85 °C from the year 1850, indicating that the average temperature of the earth’s surface has increased steadily over the past three decades and higher than every previous decade.
  • Measurement data between 1983 and 2012 indicate that the northern hemisphere has an average temperature higher than 1,400 years ago.
  • During 1901 to 2012, the average of temperature increased in all regions of the world except in certain areas of the North Atlantic.
  • The average air temperature has the highest increase in the Polar Regions of Asia and parts of Africa.
  • The amount of heat in the global climate system is more than 90% accumulated in the ocean, with the average temperature of the oceans at the surface to a depth of 75 meters, between 1971 – 2010, increased by 0.11 °C per decade or increased 0.44 °C in the past 40 years.
Extreme temperatures
  • Since 1950, the number of cold days and nights have decreased, and the number of hot days and nights have increased on a global scale.
  • The frequency of heat waves have increased in most parts of Europe, Asia and Australia.
Precipitation
  • Changes in the average precipitation in the world since 1901 found no clear trend .
  • The precipitation average in the central latitudes (between 50-60 degrees north and south) in the northern hemisphere tends to increase markedly.
Extreme precipitation
  • Areas with an increased number of heavy rainfall are of greater proportion than areas with decreasing heavy rainfall.
  • The frequency and severity of heavy rains are clearly increasing in North America and Europe.
Sea Ice Area
  • Greenland and Antarctica ice sheet sizes have continuously decreased from 1992 to 2011.
  • The loss of ice sheets occurred the most during the years 2002 – 2011.
  • Glacier, Arctic sea ice and snow cover in spring in the northern hemisphere have continuously reduced in size.
  • The annual average of the size of the Arctic sea ice region has decreased 3.5 – 4.1% per decade or 11.6 – 13.5% between 1979 and 2012.
Sea Level
  • Since the mid-19th century, sea levels have risen above the average of 2,000 previous year.
  • The highest sea level in the world in the past 129,000 – 116,000 years is at least 5 meters higher than the current level with the Greenland ice sheet contributing to rising sea levels of between 1.4 – 4.3 meters.
2.5

Trends of Change and Effects on the World in the Future

Thailand’s second assessment report on climate change 2016: Updated Climate Change Knowledge and Information of Thailand prepared by the working group 1, the Thailand Research Fund or Thailand Science Research and Innovation (TSRI), summarized the key findings in the 5th report of the Intergovernmental Panel on Climate Change (IPCC) on trends of global climate change in the future which can be summarized as follows;
Table 5-3 Trends and details of global climate change in the future
Change 
Temperature
    • • Global average surface temperature change during the late 21st century between 2081 and 2100, compared to the period 1986 – 2005 showed that the temperature tends to rise (Figure 5-12 and 5-13) as follows:
The increase in slobal average surface temperature (C)Greenhouse gas emissions situation
0.3 – 1.7Strict greenhouse gas reduction (RCP 2.6)การลดก๊าซเรือนกระจกที่เข้มงวด (RCP 2.6)
1.1 – 2.6Moderate greenhouse gas reduction and fixed radiation value of 4.5 watts per square meter(RCP 4.5)
1.4 – 3.1Moderate greenhouse gas emissions and fixed radiation values of 6.0 watts per square meter (RCP 6.0)
2.6 – 4.8Situation of high emission of greenhouse gases (RCP 8.5)
Figure 5-12 The increase in global average surface temperature at the end of the 21st century under 4 situations of greenhouse gas emissions compared to the period 1986 – 2005. (Source: TSRI, 2016)
  • The global average surface temperature at the end of the 21st century will increase more than 5C compared to the temperature in the period 1850 – 1900 for all greenhouse gas emission situations.
Figure 5-13 Trend Series of Global average surface temperature change average air temperature change of earth's surface estimated with climate models (source: IPCC, 2013)
Note
  • RCP 2.6 means situation that uses strict greenhouse gas reduction measures.
  • RCP 4.5 means situation that uses moderate greenhouse gas reduction measures and fixed radiation value of 4.5 watts per square meter.
  • RCP 6.0 means situation that moderate greenhouse gas emission measures and fixed radiation value of 6.0 watts per square meter.
  • RCP 8.5 means situation of high levels of greenhouse gas emissions (RCP 8.5) between 1950 and 2100 compared to the period 1986 – 2005.
Change Detail
Precipitation
  • The average annual precipitation at the end of the 21st century will increase in the area of latitude 60 degrees north and south including the equator at the Pacific Ocean under the situation of high emission of greenhouse gases (RCP 8.5).
  • Average precipitation amount will decrease in the central latitudes (between 50-60 degrees north and south) in many regions with Mediterranean climates.
Extreme conditions of precipitation
  • The extreme conditions of precipitation at the end of the 21st century will be more severe and occur more often in warm and tropical regions in line with the higher global average surface temperature.
  • Monsoon winds will weaken but intensity of the rain will increase due to increased humidity in the atmosphere.
  • The beginning day of the monsoon season will be faster while the end of the monsoon season will be delayed resulting in the monsoon season being longer in many regions.
Sea Ice Area
  • Arctic sea ice and snow cover in the spring in the northern hemisphere in the 21st century will be continuously reduced in size and thinness.
  • Under the high greenhouse gas emission scenario (RCP 8.5), the arctic sea ice in September will be completely melted before the middle of the 21st century.
  • The volume of glaciers which do not include glaciers in the southern hemisphere after the 21st century will decrease by:
    • 15 – 55% under the strict greenhouse gas reduction measures (RCP 2.6)
    • 35 – 85% under the high level of greenhouse gas emission (RCP 8.5)
  • Snow covered in the spring in the northern hemisphere, estimated to reduce by 7% under the strict greenhouse gas reduction measures (RCP 2.6) and 25% under the high level of greenhouse gas emission (RCP 8.5) respectively.
Sea Level
  • Under all greenhouse gas emission situations, the average sea level in the world will continuously increase by the end of the 21st century. The average sea level in the world compared to the period 1986 – 2005 will increase (details shown in Figure 5-14 and Figure 5-15)
Sea rising level (meters) Greenhouse gas emission situation
0.26 – 0.55
Strict greenhouse gas reduction (RCP 2.6)
0.32 – 0.63
Moderate greenhouse gas reduction and fixed radiation value of 4.5 watts per square meter (RCP 4.5)
0.33 – 0.63
Moderate greenhouse gas emission and fixe radiation value of 6.0 watts per square meter(RCP 6.0)
0.45 – 0.82
Situation of high emission of greenhouse gas 0.45 – 0.82
Figure 5-14 Sea level rise in the late 21st century under 4 situations of greenhouse gas emissions compared to 1986 – 2005 (Source: TSRI, 2016)
  • By 2100, sea levels will increase between 0.52 – 0.98 meters with a rate during 2081–2100 of 8 to 16 mm year under simulated scenarios of high levels of greenhouse gas emissions (RCP 8.5).
  • The increase in average global temperature with thermal expansion will result in sea level rise in the 21st century accounts for 30 – 55% of it. The melting of the Greenland and Antarctic ice sheets cause sea level rise in the range of 0.03 – 0.20 meters in the year 2081 – 2100
Figure 5-15 Estimation of increase of the average sea level in the world by 2100 (Source: IPCC, 2013)
Note
  • RCP 2.6 means situation that uses strict greenhouse gas reduction measures./li>
  • RCP 4.5 means situation that uses moderate greenhouse gas reduction measures and fixed radiation value of 4.5 watts per square meter.
  • RCP 6.0 means situation that moderate greenhouse gas emission measures and fixed radiation value of 6.0 watts per square meter.
  • RCP 8.5 means situation of high levels of greenhouse gas emissions (RCP 8.5) between 1950 and 2100 compared to the period 1986 – 2005.
2.6

Impacts and Adaptation on Climate Change

Current climate change trends in Thailand from the summary of Thailand’s First and Second Assessment Report on Climate Change by the Thailand Research Fund or Thailand Science Research and Innovation (TSRI) at present. The details are as follows:

Trends of climate change in Thailand

Temperature

  • Temperatures in Thailand have experienced a significant increase in the past 40 years (1970 – 2009), in line with the temperature rise in the Indo-Pacific region and other parts of the world.
  • The maximum temperature, mean temperature, and minimum temperature in Thailand tend to increase by 0.86๐C, 0.95๐C and 1.45๐C respectively. The lowest temperature in Thailand is increasing higher than the highest temperature and the average temperature causes the day temperature range to be significantly short.
  • The short-term fluctuations of the annual temperatures in Thailand are related to the ENZO – the temperature in Thailand during the El Nino and La Nina period being higher and lower than usual, respectively.
  • Considering the increase in regional temperatures, it was found that the eastern region had the highest temperature, followed by the central region and the southern region respectively.
  • Larger cities in Thailand, such as Bangkok, tend to increase temperatures at higher rates than non-urban areas. The heat-island effect may occur due to heat accumulation from the expansion of the city and changes in land use.

Extreme conditions of temperature

  • The extreme conditions of temperature in Thailand tend to change significantly in the 40 – 50 years between 1970 – 2009 with the same direction of either increasing or decreasing throughout the country, in line with the warming of Thailand and the changes observed in the Asia-Pacific region.
  • The extreme conditions of temperature in Thailand that tend to increase significantly (Table 5-7) are:
    • Number of warm days and nights
    • Warm period
    • Number of days when the highest temperature is above 35๐C
    • Number of nights when the lowest temperature is above 25๐C
    • Highest and lowest temperature of the day in the hottest month
    • Highest and lowest temperature of the day in the coldest month
  • The extreme conditions of temperature in Thailand that tend to decrease significantly (Figure 5-28) are:
    • Number of cold days and nights
    • Cold period
    • Daily temperature range
    • Temperature range of years
Table 5-7 Trend of changes in the extreme conditions of temperature
in 1970 – 1979
NoTemperature extreme index

trend of changes

in 1970 – 197

1.Number of warm day (day per decade) the proportion of day with the
highest temperatures above the 90th percentile
-0.6 to 9.2 (3.4)
80.0 %
2.Number of warm night (day per decade) the proportion of day with the
lowest temperature above the 90th  percentile
-0.3 to 8.8 (3.5)
83.1%
3.Number of cold day (day per decade) the proportion of day with the
highest temperature below the 90th  percentile
-3.9 to 0.1 (-1.9)
92.3%
4.Number of cold night (day per decade) the proportion of day with the
lowest temperature below the 10th  percentile
-7.5 to 0.9 (-3.0)
83.1 %
5.Number of cold day (day per decade) the number of consecutive days
at least 6 days at the lowest temperature below the 10th  percentile
-13.4 to 6.0 (-1.9)
92.3 %
6.Warm period (day per decade) the number of consecutive days for at
least 6 days at the highest temperature above the 90th  percentile
-0.5 to 19.5 (4.3)
72.3 %
7.Average minimum temperature of thedaily minimum (Degrees Celsius per
decade) Average minimum temperature of the daily minimum
-0.28 to 1.85 (0.64)
72.3 %
The temperature extreme index trend that to increase
The temperature extreme index trend that to decrease
Figure 5-28 Temperature changes in Thailand during 1970 - 2006

Rain

  • Annual cumulative rainfall in Thailand does not show a clear trend of long-term changes over the past 55 years (1995 – 2009).

  • The amount of cumulative rainfall during the summer monsoon between May and October does not show clear trends for long-term changes as well as the annual cumulative rainfall.

  • The amount of cumulative rainfall between November and April tends to increase significantly, especially in the southern region of the Gulf of Thailand which corresponds to the strong northeast monsoon at 10.8 mm. per decade or 64.8 millimeters in the past 60 years (1955 – 2014).

  • The annual cumulative rainfall in Thailand has a period of variation between years and between decades and is related to the following phenomena:
    • Monsoon
    • ENSO
    • Madden Julian Oscillation (MJO)
    • Indian Ocean Dipole (IOD)
    • Pacific Decadal Oscillation (PDO)

      The main phenomena influencing the change in rainfall in Thailand are the Asian monsoon system and ENSO, in which the El Nino has more influence on rainfall than the La Niña.

  • Regional changes found that the southern region of the Andaman Sea and the Gulf of Thailand has a tendency to change the amount of accumulated rain decreasing and increasing respectively during 1955 – 2014, while the annual regional cumulative rainfall of Eastern, Northern, Western, and Northeastern regions do not have significant trends of change.

  • The increase in cumulative rainfall in the southern region of the Gulf of Thailand coincides with the winter monsoon in East Asia. Also, there has been a change over the decades, especially the shift of the monsoon trough and the frequency of cold surges.

  • The fluctuation of the Asian winter monsoon often causes heavy rain and climate disasters in Southeast Asia. The severe flooding that occurred in southern Thailand and the southern Malaysian peninsula is a result of heavy rain induced by the Asian winter monsoon and the stronger cold surge.

Extreme conditions of rain

  • The extreme conditions of rain in Thailand have complex changes. The Index of extreme conditions of rain in the country during the 60 years between 1955 – 2014 is likely to change in the direction of increasing and decreasing.

  • The extreme conditions of rain in Thailand that tend to increase (Table 5-8) are:
    • Daily rain intensity
    • Number of heavy rain day
    • Period without rain

  •  The extreme conditions of rain in Thailand that tend to decrease (Figure 5-29) are:
    • Annual number of rainy days
    • Annual total rainfall
    • Duration of continuous rain
    • Frequency of heavy rain

  • The total amount of rain from heavy rains and the intensity of rain in each event tends to increase significantly, but the duration of continuous rain and total annual rainfall decreases significantly which decreases total annual rainfall in Thailand in the 60 years between 1955 – 2014.

  • When considering the extreme conditions of rain in Thailand in spatial conditions, it is found that the area that appears similar to the extreme conditions of the rain are smaller in comparison to the size of the areas that appear at the extreme conditions of the temperature, with the central, northern, and southern regions having the tendency to decrease significantly with respect to the number of total annual rainy days and frequency of rain.
NO Extreme Precipitation Indices Trend of changes

tin 1970 – 1979
1 Annual number of rainy days to (Percent per decade) The number to of rainy days is greater than 1 mm -12.6 to 9.9 (-0.8)
22.9% / 9.4 %
2 Annual total rainfall to  (Percent per decade) -8.0 to 7.0 (-0.96)
21.9% / 7.3 %
3 Daily rain intensity  (Percent per decade)  Annual total rainfall per total number of rainy days -10.4 to 7.7 (0.6)
5.2% / 16.7%
4 The total rainfall of heavy rain to (Percent per decade) The total to rainfall of the rain that is greater  than the percentage of 95 -33.0 to 17.9 (0.4)
5.1% / 11.5 %
5 Maximum total rainfall in 1 day to (percent per decade) Monthly total to rainfall of the day with the highest rainfall in 1 day -15.1 to 12.1 (0.04)
5.2% / 16.7%
6 Maximum total rainfall in 5 days to (percent per decade) Monthly  rainfall in the day with the highest rainfall in 5 days. -16.1 to 14.1 (-0.3)
3.1% / 5.2%
7 Number of heavy rain days (Percent per decade) The number  of rainy days is more than 10 mm -8.8 to 6.8 (-0.94)
12.5% / 4.2%
8 Period without rain continuously  (Percent per decade) The maximum  number of days that the rainfall isto less than 1 mm continuously -13.6 to 16.9 (3.5)
2.1% / 18.8 %
9 Continuous rainy period
10 The frequency of heavy rain
The extreme precipitation indices trend that to increase
The extreme precipitation indices trend that to decrease
Figure 5-29 Changes of rain in Thailand during 1955 – 2014

Tropical cyclone

  • Tropical cyclones that move into Thailand have tendencies to decrease significantly in the past 64 years (1951 – 2014) as shown in Figure 5-30, which therefore directly affects the amount of rain and drought in Thailand. On the other hand, tropical cyclones that are more intense than the depressions in every decade since the 70s tend to increase significantly, resulting in Thailand being exposed to heavy rain, flooding and drought conditions for a longer period.
Figure 5-30 The trend of the frequency of tropical cyclones that moved into Thailand in 64 years (1951 – 2014) (source: TMD, 2011 and Meteorological Department, 2015)

Sea level

  • The sea level in each area has an unequal rise rate depending on the water cycle and oceanographic processes in each area.
  • ENSO ranges between 2 – 7 years and may change sea level around the East Pacific and Indian Ocean between 20 – 30 cm. between years to a decade.
  • Sea levels near Thailand, such as the Andaman Sea, the South China Sea, and the sea in Indonesia between 1993 – 2016 have increased at the rate of 3.6 – 6.6 mm. per year or have increased 86.4 – 158.4 mm. in the past 24 years (studied from satellite altimeter).
  • Sea levels in the Gulf of Thailand between 1993 – 2009 have increased by 3.5 mm. per year or 59.5 mm. over the past 17 years (from satellite altimeter with details as in Figure 5-31).
Figure 5-31 Average sea level change rate in the Gulf of Thailand from the Altimeter data during 1993 - 2009 in millimeters per year (mm yr-1) (Source: Trisirisatayawong et al., 2011)
2.7

Future climate change trends in Thailand

The trend of temperature changes in 40 years in Thailand

          The study of climate change trends in Thailand in the future contains data from the Thailand weather simulation under 2 scenarios which are RCP4.5 and RCP8.5. The data presented is temperature and rainfall change data in Thailand, within a 40-year period (2015 – 2055).

Table 5-9 Temperature changes in Thailand under RCP4.5 and RCP 8.5 scenarios between 2015 and 2055
YearRCP4.5 RCP8.5

Temperature

Lowest average – highest average

Average

temperature (˚C)

Percentage change in 5 years

Temperature

Lowest average – highest average

Average

temperature (˚C)

Percentage change in 5 years
201521.47 – 32.0726.7532.10 – 21.5126.79
202021.64 – 32.2326.910.6032.29 – 26.9826.980.71
202521.81 – 32.3927.090.6732.48 – 27.1827.180.74
203021.99 – 32.5527.250.5932.68 – 22.1327.390.77
203522.15 – 32.7127.410.5932.90 – 22.3627.610.80
204022.32 – 32.8627.570.5833.12 – 22.6027.840.83
204522.47 – 33.0027.720.5433.35 – 22.8428.080.86
205022.62 – 33.1427.860.5133.59 – 23.1028.330.89
205522.75 – 33.2727.990.4733.84 – 23.3728.590.92

Source: Final report of Study for Climate Change Adaptation Plan, Office of Natural Resources and Environmental Policy and Planning (ONEP), January 2016

RCP4.5

The tendency of the temperature change rate is to increase at the beginning and then gradually decrease, causing the temperature change for RCP4.5 not to be severe but instead stable and decreasing in subsequent steps.

RCP8.5

Temperature change in Thailand from the simulation with RCP8.5 found that the tendency of temperature changes will continue to increase.

Table 5-10 Total rainfall in Thailand under RCP4.5 and RCP8.5 scenarios between 2015-2055
ปี RCP4.5 RCP8.5
Average total rainfall in the whole country (mm) Percentage change in 5 years Average total rainfall in the whole country (mm) Percentage change in 5 years
2015 1,509.90 1,511.69
2020 1,517.93 0.53 1,520.80 0.60
2025 1,525.94 0.53 1,530.39 0.63
2030 1,533.85 0.52 1,540.46 0.66
2035 1,541.60 0.51 1,550.99 0.68
2040 1,549.09 0.49 1,561.97 0.71
2045 1,556.26 0.46 1,573.40 0.73
2050 1,562.03 0.43 1,585.25 0.75
2055 1,569.31 0.40 1,597.52 0.77
Final report of Study for Climate Change Adaptation Plan, Office of Natural Resources and Environmental Policy and Planning (ONEP), January 2016

RCP4.5 and RCP8.5

The total rainfall throughout the year in Thailand in the situation RCP4.5 is likely to increase in 40 years in the future.

 

Climate analysis for standard years during 1981-2010


The variety of topography and climate patterns in Thailand are relatively small. According to the Meteorological Division of Thailand, Thailand can be divided into 5 regions based on the climate patterns as follows:

  • Northern region consists of 15 provinces which are Chiang Rai, Mae Hong Son, Chiang Mai, Lamphun, Lampang, Phayao, Nan, Phrae, Uttaradit, Sukhothai, Tak, Kamphaeng Phet, Phitsanulok, Phichit and Phetchabun.
  • Northeastern region consisting of 20 provinces which are Nong Khai, Bueng Kan, Loei, Nong Bua Lamphu, Udon Thani, Sakon Nakhon, Nakhon Phanom, Mukdahan, Kalasin, Khon Kaen, Maha Sarakham, Roi Et, Yasothon, Amnat Charoen, Chaiyaphum, Nakhon Ratchasima, Buri Ram, Surin, Sisaket and Ubon Ratchathani.
  • Central region consists of 18 provinces which are Nakhon Sawan, Uthai Thani, Chai Nat, Singburi, Lopburi, Ang Thong, Saraburi, Suphanburi, Phra Nakhon Si Ayutthaya, Kanchanaburi, Ratchaburi, Nakhonpathom, Nonthaburi, Pathum Thani, Bangkok, Samut Prakan, Samut Songkhram and Samut Sakhon.
  • Eastern region consists of 8 provinces which are Nakhon Nayok, Chachoengsao, Prachinburi, Sa Kaeo, Chon Buri, Rayong, Chanthaburi and Trat.
  • Southern region is a peninsula flanked by two sides sea. The west side is the Andaman Sea. The east side is the Gulf of Thailand. This region is divided into 2 parts as follows:
    • The east side of the southern region is the upper part of the continuation to the eastern coastal plain, consisting of 10 provinces: Phetchaburi, Prachuap Khiri Khan, Chumphon, Surat Thani, Nakhon Si Thammarat, Phatthalung, Songkhla, Pattani, Yala, and Narathiwat.
    • The west side of southern region consists of 6 provinces, namely Ranong, Phang Nga, Phuket, Krabi, Trang and Satun.

 

The criteria for determining the amount of rainfall in the 24-hour period of each day starting at 07.00am according to the characteristics of rain falling in tropical countries in the monsoon area are as follows:

  • Unmeasurable rainfall of less than 0.1 mm.
  • Light rainfall between 0.1-10.0 mm.
  • Moderate rainfall between 10.1-35.0 mm.
  • Heavy rain between 35.1-90.0 mm.
  • Very heavy rain of rain is 90.1 mm and over.

The weather in the summer is determined by the maximum temperature of each day, with the following criteria considered:

  • Hot weather with temperatures between 35.0 and 39.9˚C and;
  • Extremely hot with temperatures from 40.0˚C and above.

Weather conditions in winter are determined by the minimum temperature of each day. The criteria for consideration are as follows:

  • Extream cold with temperatures below 8.0˚C;
  • Cold with temperatures between 8.0 and 15.9˚C and;
  • Cool air, the temperature between 16.0 and 22.9˚C

The general Thai season can be divided into 3 seasons as follows:

  • Summer between mid-February to mid-May;
  • Rainy season between mid-May to mid-October and;
  • Winter between mid-October to mid-February.

Analyzing results from monthly climate models for Thailand for the next 40 years – Period 1 (2016-2035) and Period 2 (2036-2055):

1. Rainfall

Table 5-11 Rainy period in Thailand by region in the future for 40 years – period 1 (2016-2035)
Period 1 (2016-2035)
Region Rainy period Maximum rainfall
Less than 90.0 mm. More than 90.1 mm.
North January to April and November to December May to October 896.7 mm In July 2034 At Mae Sot Meteorological Station, Tak Province
Northeast January to April and November to December May to October 852.1 mm In August 2025 At Nakhon Phanom Meteorological Station, Nakhon Phanom Province
Central region January to April and November to December May to October 669.7 mm In July 2017 At Thong Pha Phum Meteorological Station, Kanchanaburi Province
East January to March and November to December April to October 2,131.6 mm In July 2017 At Khlong Yai Meteorological Station, Trat Province
East coast of Southern region January to April May to December 1,258.6 mm In December 2025 At Meteorological Station, Mueang District, Songkhla Province
West coast of Southern region January to February and December March – November 1,237.4 mm In August 2017 At Meteorological Station, Mueang District, Ranong Province
Period 1 (2036-2055)
Region Rainy period Maximum rainfall
Less than 90.0 mm. More than 90.1 mm.
North January to April and November to December May to October 926.7 mm In July 2054 At Mae Sot Meteorological Station, Tak Province
Northeast January to April and November to December May to October 842.5 mm In June 2042 At Nakhon Phanom Meteorological Station, Nakhon Phanom Province
Central region January to April and November to December May to October 678.4 mm In July 2037 At Thong Pha Phum Meteorological Station, Kanchanaburi Province
East January to March and November to December April to October 2,089.0 mm In July 2037 At Khlong Yai Meteorological Station, Trat Province
East coast of Southern region January to April May to December 1,184.2 mm In December 2045 At Meteorological Station, Mueang District, Songkhla Province
West coast of Southern region January to February and December March – November 1,195.9 mm In August 2037 At Meteorological Station, Mueang District, Ranong Province
Note: The monthly rainfall is less than 90.0 mm, meansing in the period of light rain and moderate rain to heavy rain, rainfall is greater than 90.1 millimeters.

2. The highest air temperature

Table 5-13 The highest average monthly air temperature in Thailand in the future for the next 40 years, period 1 (2016-2035)
Period 1 (2016-2035)
RegionThe period with the highest average monthly air temperature rangeHighest temperature
35.0-39.9°CMore than 40.0°C
NorthMarch – MayNot found to happen at any time42.9 °C in 2035 at Mae Hong Son Meteorological Station, Mae Hong Son Province
NortheastMarch – MayNot found to happen at any time

41.7 °C in 2032

at Tha Tum Meteorological Station, Surin Province

Central regionFebruary – MayNot found to happen at any time43.7 °C in 2032 at Kanchanaburi Meteorological Station, Kanchanaburi Province
EastAprilNot found to happen at any time41.2 °C in 2032 at Aranyaprathet Meteorological Station, Prachinburi
East coast of Southern regionNot found to happen at any timeNot found to happen at any time39.0 °C in 2032 at Surat Thani Meteorological Station Surat Thani Province
West coast of Southern regionMarchNot found to happen at any time40.0 °C in 2032 at Trang Meteorological Station, Trang Province



Table 5-14 the highest average monthly air temperature in Thailand in the future for the next 40 years, period 2 (2036-2055)
Period 2 (2036-2055)
Region The period with the highest average monthly air temperature range Highest temperature
35.0-39.9°C More than 40.0°C
North February – May Not found to happen at any time 43.3 °C in 2050 at Mae Hong Son Meteorological Station, Mae Hong Son Province
Northeast March -July Not found to happen at any time 41.6 °C in 2052 at Tha Tum Meteorological Station, Surin Province
Central region February – July Not found to happen at any time 43.3 °C in 2052 at Kanchanaburi Meteorological Station, Kanchanaburi Province
East March – May Not found to happen at any time 41.1 °C in 2052 at Aranyaprathet Meteorological Station, Prachinburi
East coast of Southern region April – May Not found to happen at any time 39.2 °C in 2038 at Surat Thani Meteorological Station Surat Thani Province
West coast of Southern region February – April Not found to happen at any time 40.1 °C in 2038 at Trang Meteorological Station, Trang Province
Note: The highest average monthly air temperature between 35.0-39.9 °C means hot weather. The highest average monthly air temperature is over 40.0 °C meaning it is extremely hot.

3. The lowest air temperature

Table 5-15 The Lowest average monthly air temperature in Thailand for the next 40 years, period 1 (2016-2035)
Period 1 (2016-2035)
Region The period with the lowest average monthly air temperature between 16.0-22.9 °C Lowest temperature
North January – March and October – December 10.0 °C in 2016 at Umphang Meteorological Station, Tak Province
Northeast January – February and November – December 13.1 °C in 2029 at Loei Meteorological Station, Loei Province
Central region January and November – December 14.1 °C in 2023 at Thong Pha Phum Meteorological Station, Kanchanaburi Province
East January and December 18.7 °C in 2029 at Kabinburi Meteorological Station, Prachinburi
East coast of Southern region Not found to happen at any time 19.3 °C in 2017 at Prachuap Khiri Khan Meteorological Station Prachuap Khiri Khan Province
West coast of Southern region Not found to happen at any time 20.8 °C in 2030 at Trang Meteorological Station, Trang Province
Table 5-16 The Lowest average monthly air temperature in Thailand for the next 40 years, period 2 (2036-2055)
Period 1 (2016-2035)
Period 1 (2016-2035)
RegionThe period with the lowest average monthly air temperature between 16.0-22.9 °CLowest temperature
North

January – March

and

November – December

11.3 °C in 2052 at Umphang Meteorological Station, Tak Province
Northeast

January – February

and

November – December

14.7 °C in 2049

at Loei Meteorological Station, Loei Province

Central regionJanuary and December15.3 °C in 2043 and 2053 at Thong Pha Phum Meteorological Station, Kanchanaburi Province
EastNot found to happen at any time20.1 °C in 2039 at Prachinburi Meteorological Station, Prachinburi
East coast of Southern regionNot found to happen at any time20.3 °C in 2037 at Prachuap Khiri Khan Meteorological Station Prachuap Khiri Khan Province
West coast of Southern regionNot found to happen at any time21.5 °C in 2050 at Trang Meteorological Station, Trang Province
Note:

The Lowest average monthly temperature between 16.0-22.9 ° C translates to cold weather.

4. Average air temperature

Table 5-17 Average seasonal air temperature in Thailand for the future 40 years, period 1 (2016-2035)
Period 1 (2016-2035)
Region Average seasonal air temperature Average high air temperature Average low air temperature
Summer Rainy Winter
North 28.3-30.3 °C 26.3-29.4 °C 22.9-26.3 °C 30.3 °C in April 22.9 °C in December
Northeast 29.7-30.4 °C 28.2-29.4 °C 24.1-26.7 °C 30.4 °C in April 24.1 °C in January and December
Central region 30.2-31.4 °C 28.7-29.5°C 26.3-28.8 °C 31.4 °C in April 26.3 °C in December
East 29.5-30.4°C 28.6-29.9 °C 27.1-27.8 °C 30.4 °C in April 27.0 °C in December
East coast of Southern region 28.6-29.4 °C 28.1-29.2 °C 26.6-27.5 °C 29.4 °C in April 26.6 °C in December
West coast of Southern region 29.2-29.4 °C 27.7-29.1 °C 27.4-27.9 °C 29.4 °C in April 27.5 °C in December
Table 5-18 Average seasonal air temperature in Thailand for the future 40 years, period 2 (2036-2055)
Period 1 (2016-2035)
Region Average seasonal air temperature Average high air temperature Average low air temperature
Summer Rainy Winter
North 29.3-31.4 °C 27.6-29.2 °C 24.2-26.5 °C 31.4 °C in April 24.2 °C in January and December
Northeast 30.2-31.6 °C 29.2-30.4 °C 25.2-28.1 °C 31.6 °C in April 25.2 °C in December
Central region 31.0-32.3 °C 29.5-30.5 °C 27.5-28.9 °C 32.3 °C in April 27.5 °C in December
East 30.2-31.1 °C 29.3-30.8 °C 28.0-28.6 °C 31.1 °C in April 28.0 °C in December
East coast of Southern region 29.3-30.3 °C 28.9-30.1 °C 27.3-28.2 °C 30.3 °C in April 27.3 °C in December
West coast of Southern region 29.9-30.3 °C 28.5-29.9 °C 28.0-28.8 °C 30.3 °C in April 28.0 °C in October
Comparison of climate characteristics during the normal 30-year standard, between 1981-2010 and the results from future 40-year forecasting models between 2016-2055 during different periods. Comparison of the results of the monthly regional meteorological variables in the future for the 40 years between 2016-2055 divided into 2 periods of 20 years and divided into 8 periods of 5 years, respectively, with a 30-year standard mean between 1981-2010 provided by the Meteorological Department – details as follows:

1. Rainfall

In conclusion, in all regions of Thailand, the future trend of monthly rainfall (blue line) is close to the 30-year average (red line) during the first 7 months, after which the amount of rainfall will increase significantly during the last 5 months, especially during the rainy season. Apart from the east coasts of the southern region the (Blue line), the country is close to the 30-year average (red line) in the first 9 months, after which it is clearly less than the average for the last 3 months.

Example: Future comparison of regional monthly rainfall results

Figure 5-32 Monthly total rainfall for various annual periods in northern Thailand, period 1
Figure 5-33 Monthly total rainfall for various annual periods in northern Thailand, period 2
Figure 5-34 Monthly total rainfall for various annual periods in the eastern side of south of Thailand, period 1
Figure 5-35 Monthly total rainfall for various annual periods in the eastern side of south of Thailand, period 2
The highest air temperature In conclusion, all regions of Thailand tend to have the highest average monthly air temperature in the future (blue line), higher than the 30-year average (red line) throughout the 12 months of the period of about 2 °C. For the average temperature of the 5-year period, it is found that every period is clearly higher than the 30-year average for the whole 12 months. Example Comparison of the highest monthly average air temperature in the future by region
Figure 5-36 Monthly average highest air temperature for various annual periods in the eastern part of Thailand, period 1
Figure 5-37 Monthly average highest air temperature for various annual periods in the eastern part of Thailand, period 2
The lowest air temperature In conclusion, all regions of Thailand tend to have the lowest average monthly air temperature in the future (blue line), higher than the 30-year average (red line) during the first 9 months of about 1 °C with the last 3 months being close to the average. For the average temperature of the 5-year period, it was found that every period was higher than the 30-year average. Example Future comparison of the lowest monthly average air temperature in the future by region
Figure 5-38 Monthly average lowest air temperature for various annual periods in northeastern of Thailand, period 1
Figure 5-39 Monthly average lowest air temperature for various annual periods in northeastern of Thailand, period 2
Average air temperature All regions of Thailand tend to have monthly average air temperature in the future (blue line) higher than the 30-year average (red line) during the first 9 months of about 1 °C whilst the last 3 months are close to the average. For the average temperature of 5-year period, it was found that every period was higher than the 30-year average. Example: Comparison of monthly average air temperature in the future by region
Figure 5-40 Monthly average air temperature for various annual periods in the central region of Thailand, period 1
Figure 5-41 Monthly average air temperature for various annual periods in the central region of Thailand, period 2
Forecasting future climate change for the next 40 years, period 1 (2016-2035) and period 2 (2036-2055) of Thailand
1. Temperature change The results from forecasting temperature changes from the mathematical models were analysed by first dividing the analysis period into 20 years per period, then showing the monthly maximum temperature change forecast of each period. It also illustrated the changing areas as different levels and the average maximum temperature change compared to the 30-year standard between 1981-2010 as shown in Figure 5-42 and Figure 5-43.
Figure 5-42 The average level of maximum temperature change from the base year during 2016 – 2035
Figure 5-43 The average level of maximum temperature change from the base year during 2036 – 2055
Figure 5-44 The average minimum temperature change from the base year during 2016 – 2035
Figure 5-45 The average minimum temperature change from the base year during 2036 – 2055
Figure 5-46 The average temperature change from the base year during 2016 – 2035
Figure 5-47 The average temperature change from the base year during 2036 - 2055
Change in maximum rainfall The results from the forecast of rainfall change from the mathematical model obtained from the analysis are divided into 20 years for each analysis, showing the monthly forecasted rainfall change in each period and illustrating the areas of varying levels and the average maximum rainfall as shown in Figure 5-48 and Figure 5-49.
Figure 5-48 Change of average maximum rainfall from the base year during 2016 – 2035
Figure 5-49 Changes in average maximum rainfall from the base year during 2036 - 2055
2.8

Variation and Climate Phenomena Linking Climate Change in Thailand

Climate Variability refers to climate patterns that deviate from normal values and can last annually to many decades and is the result of global, regional and local climate phenomena (Figure 5-16). Thailand, located on the Indochina peninsula adjacent to the Pacific and Indian Oceans, is influenced by the fluctuations of climate phenomena that occur from both oceans in the form of climate change phenomena in various times. In addition, climate variability, also the cause of extreme weather and natural disasters both at the regional and local levels, is considered an important part of climate change because it is a short-term variation that can affect various sectors in a wide range.
Figure 5-16 Climate Variability and Climate change (Modified from Environment Canada, 2012)

Climate phenomena

Climate phenomenon is the interaction between the atmosphere, the ground and the ocean surface, causing extreme conditions of the weather and natural disasters. Climate phenomena that occur in each region and climate variability are linked through a remote linkage process, which, by understanding climate phenomena, can help predict future changes. The important climatic phenomena that occur in Thailand include;
  1. Monsoons
  2. El Niño – Southern Oscillation; ENSO
  3. (Indian Ocean Dipole; IOD
  4. Madden Julian Oscillation (MJO)
1. Monsoons

are the seasonal winds in Thailand, caused by the difference in temperature between the air mass in the ground and the water, resulting in the circulation of seasonal wind. In winter, the air temperature above the ground is colder than the water – the air above the water with the higher temperature therefore floats up. In summer, the air temperature above the ground is higher than the water surface, causing the wind to blow in the opposite direction. For Thailand, it is under the influence of 2 types of monsoon winds which are (1) The Summer monsoon (Southwest monsoon) prevailing over Thailand between mid-May and mid-October. This monsoon will bring moist air mass from the Indian Ocean to Thailand and crash into the mountains, causing heavy rain especially in the southern Andaman coast and (2) The Winter monsoon (Northeast monsoon) which prevails over Thailand from mid-October to mid-February (after the influence of the Summer monsoon). This monsoon will blow cool and dry air from Mongolia and China to cover Thailand, resulting in cold and dry weather in the north and northeast. The southern region will have abundant rainfall, especially in the east coast, as this monsoon blows the moist air mass from the Gulf of Thailand to cover (Figure 5-17).

Figure 5-17 Summer Monsoon and Winter Monsoon (Source: The Thailand Research Fund, 2011)

2. El Niño – Southern Oscillation; ENSO

or EN + SO is a term to describe the El Niño and Southern Oscillation. ENSO is the fluctuation in ocean surface temperatures in the Pacific.In normal conditions, the northeast and southeast winds that cover the tropical areas of the Pacific Ocean blow warm currents from east to west, creating warm water mass in Southeast Asian waters, where moisture and rain make this area abundant.

El Niño, known as the drought of the ENSO, is caused by the trade wind blowing over the equator of Pacific Ocean weakening, causing warm currents to flow from the western Pacific Ocean to South America, resulting in an area of increased cloud formation and rainfall.

On the other hand, La Niña is a reversal phenomenon with El Niño. The La Niña is caused by the strength of the trade wind, which results in warm currents being blown into the Western Pacific, resulting in increased cloud formation and rainfall (Figure 5-18). During this period, between 1900 – 2019, no less than 30 El Niños and severe phenomena occurred in the years 1982 – 1983, 1997 – 1998 and 2014 – 2016.

ENSO is linked to the fluctuations of climate systems in the southern hemisphere. The pressure above sea level in the Pacific Ocean in the southern hemisphere is related to the pressure in the Pacific Ocean on the west coast of Australia. The general index used to indicate the ENSO condition is the Southern Oscillation Index (SOI). SOI is defined as the difference between sea level pressure in Tahiti (the Pacific Ocean pressure system in the southern hemisphere) and Darwin on the west coast of Australia (the Western Pacific Pressure Systems). When the SOI index is negative (positive) for a reasonable amount of time and the standard deviation high (low) than 1 (-1), the El Niño (La Niña) phenomenon occurs. However, ENSO can still be identified by other indexes such as the Multivariate ENSO Index (MEI) which is an index derived from 6 main variances: sea surface temperature, air temperature, pressure above sea level, surface winds in the north-south, Surface wind in the east-west and the amount of cloud cover or the index that uses the irregular temperature of the sea surface in the middle of the Pacific equator, for example Nino 3.4, which is the area between latitude 5๐N – 5๐S and longitude 120๐ – 170๐W etc. (Figure 5-19). In addition, the impact of the ENSO on weather fluctuations in Thailand shows that the average air temperature tends to increase (decrease) in the year of El Niño (La Niña) and the amount of annual rainfall tends to decrease (increase) in the year of El Niño (La Nina) (Figure 5-20 and Table 5-2).

Figure 5-18 ENSO
รูปที่ 22 ดัชนีที่ใช้ค่าความผิดปกติของอุณหภูมิผิวน้ำทะเลบริเวณตอนกลางของมหาสมุทรแปซิฟิกในเขตศูนย์สูตร
Figure 5-20 Trends of temperature changes and annual cumulative rainfall caused by ENSO
Trends of temperature changes and annual cumulative rainfall while El Niño and La Nina occured
Variable El Niño La Niña
Temperature trend Increase Decrease
Annual cumulative rainfall Decrease Increase

3. Indian Ocean Dipole; IOD

is a variation of the sea surface temperature in the Indian Ocean. In normal conditions, the eastern side of the Indian Ocean or Southeast Asia is a region of warm water that is driven by Kelvin waves blowing cold water masses from the west to the southeast, causing abnormal cooling of the sea surface temperature in the southeast and the unusual warming of the surface water temperatures west of the Indian Ocean equator. In general, the IOD indicator is usually based on the Dipole Mode Index (DMI), which is water temperature difference between the west and southeast of the Indian Ocean. DMI is used to refer to the IOD. If the IOD is positive (negative), the east coast of the Indian Ocean in Southeast Asia will be dry (heavy rain) and the west side will have heavy rain (dry) as shown in Figure 5-19. The most positive IOD occurred in October 2006, while the negative occurred in July 2016.

IOD has an impact on Thailand ‘s climate – both temperature and rainfall, but the mechanism or its linkage cannot be clearly proven like the ENSO. The effects of the IOD may be part of the increase or decrease of the ENSO effect.

Figure 5-21 Trends of sea temperature changes and cumulative rainfall caused by the Indian Ocean Dipole (IOD)
Table 5-5 Trends in cumulative rainfall changes in each period related to the Indian Ocean Dipole 
RainfallTrend
The amount of rainfall accumulated during the rainy season.Increase
The amount of rainfall accumulated during the dry season (Next season)Decrease
Annual cumulative rainfallIncrease
Madden-Julian Oscillation (MJO) is a systematic formation of clouds called positive MJO, alternating with high pressure and drought, known as negative MJO, which occurs in the tropics over the Indian Ocean and moves through the east until decay in the Western Pacific Ocean (Figure 5-22) with an occurrence period between 20-100 days. MJO has the influence of changing the intensity and movement of tropical cyclones and causing fluctuations in the monsoon season, as well as stimulating the long-distance connection of the atmosphere outside of the tropical zone. The study of the development of MJO, which is measured by satellite, is represented in the area of rain clouds. It is found that the area of Thailand is affected by the MJO in both the southwest monsoon season and the northeast monsoon season which has changed in the area affected by the monsoon season.
Figure 5-22 The trend of the amount of rain caused by the Madden Julian Oscillation.
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